A hybrid of genetic transform and hyper-rectangle search strategies for evolutionary multi-tasking

作者：

Highlights：

• A novel evolutionary multi-tasking algorithm MFEA-GHS is proposed.

• Genetic transform is introduced to facilitate knowledge transfer.

• Hyper-rectangle search is proposed to balance exploration and exploitation.

• MFEA-GHS is efficient at solving various multi-factorial optimization problems.

摘要

•A novel evolutionary multi-tasking algorithm MFEA-GHS is proposed.•Genetic transform is introduced to facilitate knowledge transfer.•Hyper-rectangle search is proposed to balance exploration and exploitation.•MFEA-GHS is efficient at solving various multi-factorial optimization problems.

论文关键词：Evolutionary multitasking,Genetic transform,Opposition-based learning,Evolutionary algorithm

论文评审过程：Received 16 January 2019, Revised 7 July 2019, Accepted 8 July 2019, Available online 13 July 2019, Version of Record 19 July 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.07.015